Bibliographic record
Abstract
A solicitud de la direccion de La Otra Economia, acepte con prontitud escribir en cada numero de la revista una cronica sobre la economia social y solidaria (ESS) en America del Norte. Para mi primera cronica, me vino la idea de compartir algunas reflexiones sobre los retos del “mapeo” de la ESS tomando algunas ensenanzas de las experiencias de mapping que hemos conocido estos ultimos anos en Quebec y en Canada dentro de nuestros equipos de investigacion en partenariat sobre la ESS. Para tal efecto, tengo la intencion de hacer tres cosas en el texto siguiente. En principio, recordar el contexto en el cual la cuestion del mapping despierta mi curiosidad. Luego, explicar porque una reciente contribucion latinoamericana puede constituir un punto de referencia estimulante para nuestra reflexion critica sobre el mapping en Canada. Finalmente, presentar un balance y las ensenanzas de experimentaciones que nosotros hemos tenido en Quebec y Canada concernientes al mapping en el curso de la ultima decada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".